6 December 2007. A new type of genetic analysis has uncovered novel risk factors for schizophrenia. Writing in this week’s PNAS online, researchers led by Todd Lencz and Anil Malhotra at the Zucker Hillside Hospital, Glen Oaks, New York, report that specific runs of homozygosity (ROH)—regions of DNA where individuals inherited the identical material from both parents—are more prevalent in patients with schizophrenia. Some of these runs contain or lie close to genes that have been previously implicated in the disease, while others may harbor new genetic risk factors. The new analysis, called whole-genome homozygosity association (WGHA), is better able to find associations with recessive alleles than traditional methods, according to Lencz. “The data suggest that in a certain subset of patients, schizophrenia could resemble an autosomal, recessive disorder,” he told SRF, though he cautioned that these findings need to be replicated. (These results were covered in brief in SRF meeting summaries from the 2007 WCPG and 2007 ICOSR.)

Whole-genome homozygosity association is an extension of the whole-genome association (WGA; also known as genomewide association, or GWA) studies with which researchers are already familiar. In the latter, DNA arrays, which can simultaneously identify more than 500,000 single nucleotide polymorphisms (SNPs), are used to compare genotypes among cases and controls. WGA has emerged as a powerful way to find single SNP variations that associate with disease. In fact, Lencz and colleagues were the first to apply this technology to the study of schizophrenia (see SRF related news story). But now they have taken WGA technology one step further. Instead of focusing on single SNPs, the researchers look for clusters of SNPs that show no variation in a given individual, then ask if any of these homozygosity runs are related to disease, in this case schizophrenia.

Lencz and colleagues first looked for runs of homozygosity that were common among 144 normal Caucasian controls. An ROH was defined as any segment of DNA with 100 or more consecutive SNPs that are identical in at least 10 individuals. Using this criterion, the researchers identified 339 common ROHs in their sample population. Nine of them were very common, appearing in over 25 percent of the controls.

To validate their findings, the researchers compared ROHs from their population with data from the human HapMap project (see SRF related news story). They predicted that ROHs in their Caucasian sample set should overlap with ROHs in the HapMap European sample set, but less so in the Asian and African sample sets. Sure enough, they found that of the 32 ROHs identified in the HapMap data, all but one coincided with ROHs found in the Zucker Hillside Hospital cohort. In addition, the four most common ROHs detected from the European HapMap data were also among the five most common ROHs in the hospital data set. In contrast, ROHs from the African HapMap data showed no commonality with the hospital dataset, and though there was some overlap with ROHs identified in the Asian HapMap dataset, the most common Asian ROH was only the fortieth most common in the hospital cohort. As a whole, these relationships turned out as one might predict based on differences in population ancestry and, the authors write, suggest that the ROHs identified in the Zucker Hillside Hospital cohort do not arise because of some technical artifact.

With this validation, Lencz and colleagues next asked how ROHs are represented among a sample set of 178 Caucasian schizophrenia cases that were age- and sex-matched to the 144 controls. They found that nine ROHs occurred in patients at significantly different frequencies than in controls—all nine were more represented in patients. One ROH, harboring the gene for dynein cytoplasmic 2 heavy chain 1 protein (DYNC2H1) on chromosome 11, was found exclusively in patients (in 8 percent of cases), while five other ROHs were very uncommon in controls.

What do these new data tell us about schizophrenia? For one thing, they may bolster previously reported genetic associations. A check of SchizophreniaGene showed the researchers that four of the nine ROHs that are more common in patients harbor or are in close proximity to genes previously associated with the disease. These genes include NOS1AP, coding for a protein that binds to neuronal nitric oxide synthase and which may modulate glutamate receptor activity; ATF2, coding for activating transcription factor 2, which is elevated in postmortem brain samples (see Kyosseva et al., 2000); the NSF gene, coding for N-ethylmaleimide-sensitive fusion, a protein that binds to glutamate AMPA receptors (see Mirnics et al., 2000); and PIK3C3, the gene for phosphoinositide-3-kinase, class 3. The other five ROHs may contain novel genes that could be risk factors for schizophrenia. The MAPT gene encoding the microtubule binding protein tau, is one example. Tau has been linked to numerous and neurological disorders, including Alzheimer’s disease, and supranuclear palsy.

But the research may have broader implications, too, and not just for schizophrenia. It hints that the extent to which a person is homozygous at any given locus may put them at risk, suggested Lencz. “When you are heterozygous there is a 100 percent chance that you have at least one copy of the ‘optimal’ variant in a gene; homozygosity may result in missing an allele that can be critical for healthy development,” he said. Interestingly, while 55 percent of controls had none of the nine risk ROHs, only 19 percent of patients were risk ROH free. Furthermore, the researchers calculated that as the number of risk ROHs increases, so does the relative risk of having the disease, such that in those with three risk ROHs (14 percent of cases and only 2 percent of controls), the odds ratio of having schizophrenia increased to 24.

Of course, being homozygous means that the same allele has been inherited from both parents, which is the case in many simple autosomal recessive disorders. In general, such disorders are much rarer than schizophrenia, occurring in about 0.01 percent of the population (for schizophrenia, estimates hover around 1.0 percent), and studies on genetic transmission suggest that schizophrenia does not follow a simple Mendelian pattern. But it is possible that in a subset of patients, schizophrenia is caused by a simple recessive inheritance, Lencz suggested, though he stressed that it is more likely that these recessive ROHs just increase a person’s risk for getting the disease. “The main point is that ROHs may be overrepresented in schizophrenia and that the disease might particularly relate to those regions of the genome,” said Lencz. He also said that he is eager to engage the field in replication of these studies so as to get a better estimate of effect sizes.—Tom Fagan.

Schizophrenia as genetic pelmanism
If you take a brand new pack of cards and start shuffling, it is not hard to appreciate that the longer you continue, the less likely it will be that you will find a series of cards in the same order as in the beginning. The European and Asian genomes are like a pack of cards that effectively started shuffling as humans first walked “Out of Africa” some 100,000 years ago. Meiotic recombination is the shuffling process and the result is a decreasing ability to predict at the gross level what combinations of marker alleles will be found together on a chromosome. African populations, with a longer “shuffling” time and without population bottlenecks (which effectively reorder the cards) show the least predictability (“linkage disequilibrium,” LD) across their genomes.

There are two counteracting forces to halt or even reverse this entropic breakdown. Firstly, if a particular region becomes strongly selected for, then its frequency increase in the population will, in the medium-term, outrun the shuffling effect such that the region flanking the selected genetic variant will maintain its order (Gibson et al., 2006; Li et al., 2006). This is known as a “selective sweep,” and numerous post-HapMap studies have successfully fished out regions of our genomes under this selective pressure (e.g., the lactose tolerance variant in populations where milk became a part of the staple prehistoric diet (Tishkoff et al., 2007). Secondly, and rather more obscurely, there can be physical restraints to recombination shuffling. These usually involve the physical reordering of sequence on our chromosomes, for example, in the case of paracentric inversions. The physical alignment of normal and inverted DNA sequences during meiosis is thus prevented and so recombination is suppressed, leading to greater LD.

Now imagine the situation where reasonably common stretches of less-shuffled chromosomes exist in the population. These are more likely to be found as matching pairs in any given individual compared to other parts of the genome. This appears to the researcher as a long stretch or tract of homozygous DNA. Such tracts have been studied elsewhere, particularly in the context of mapping and identifying recessive disease genes in remote, consanguineous (inbred) populations where the recessive mutations in genomic DNA of reduced allelic complexity are not only more likely to be exposed but occur within prominent tracts which co-segregate with the diagnosis.
A newly published paper by Lencz et al. takes all of these ideas and combines them into a single strategy to hunt for schizophrenia-causing genes. They took raw data from their recently published genomewide association study of schizophrenia (178 cases of schizophrenia and 144 healthy controls: Lencz et al., 2007) and reassessed it for the presence of long “runs of homozygosity” (ROH) restricted to the case group. Their hypothesis was that if these regions existed, they would contain recessive mutations contributing to the disease.

Three hundred thirty-nine common ROHs were identified in the study, making up 12-13 percent of the total genome. The largest of these were predominantly found spanning the chromosome centromeres. This is perhaps not surprising since recombination rates have long been known to be reduced (through repression rather than selective sweep) at centromeres (see Kong et al., 2002). Nine of the commonest ROHs neatly overlap with previously described regions from selective sweep studies, as would be predicted. The key finding, however, was that when ROHs were compared between cases and controls, nine were found significantly more frequently in schizophrenia. Within these tracts, numerous genes were identified and, of these, there is pre-existing evidence in support of a few of them as potential candidates including NOS1AP, ATF2, NSF, MAPT, PIK3C3, and SNTG1.

One caveat to these findings is that a region of homozygosity, a loss of heterozygosity, copy number variation (CNV), and a deletion can, in some instances, all refer to the same genomic lesion and are not simple to distinguish by chip-based genotyping. The authors are careful to spell out technical and biological reasons for believing that their findings are a reflection of true homozygosity, but further independent verification would be reassuring, particularly in the context of how CNVs/genomic rearrangements might complicate recombination rates.

The significance of these findings is that we now have the potential to explore a brand new mutation class in a complex genetic disorder. Until now, the major research techniques such as linkage, association, and cytogenetics have only identified (and perhaps can only identify) dominantly behaving variants, albeit mostly with reduced penetrance. These are presumed to act through gain-of-function or, more likely, loss-of-function/haploinsufficiency mechanisms. The ROH regions described here are predicted to house reasonably common recessive risk variants: such properties meaning that they are not likely to be present in ascertained families with high densities of affected individuals but rather sporadic cases of illness where these alleles have, by chance, been inherited from both parents. It is not entirely clear why some of the more common ROHs didn’t feature in the original association study based on this data, particularly in genotype frequency rather than allele frequency analyses.

Nevertheless, the authors also make an additional, intriguing claim that these ROHs are not only overrepresented in the schizophrenia cohort because they are causative but because they have also been subject to positive selection. They cite the discovery of these ROHs in previous selective sweep scans, their more recent derivation from ancestral haplotypes, the presence of genes within which show selection pressure through alternative analyses, and their restriction to Caucasian populations as good evidence for such a claim. This effect may be due to some form of “heterozygote advantage” (also known as “overdominance”) which maintains or promotes the deleterious allele in the population. Examples where this phenomenon has been observed include recessive mutations giving rise to sickle-cell anemia, cystic fibrosis, and triose phosphate isomerase deficiency. Others have previously hypothesized that selection for the greater cognitive abilities in Homo sapiens compared to earlier hominins might have been at the cost of the emergence of schizophrenia, although the timescales of this kind of selection and the kind resulting in selective sweep are likely to be vastly different. An alternative explanation discussed in the paper is that rare recessive mutations could have “hitchhiked” their way to prominence within the selective sweep driven by a favorable variant in a closely linked gene. This latter idea seems more reasonable, given the difficulty in trying to imagine what cognitive or neurodevelopmental features would have been exclusively beneficial for the Caucasian population. It might also tally with some of the phenotypic epiphenomena that may coexist with schizophrenia (e.g., altered risk of rheumatoid arthritis, etc).

Finally, as an aside, this represents the third method of analysis, after the principal case-control studies and prediction of copy number variants, which can be applied to the large genomewide genotyping datasets being produced in numerous labs. Are there other aces waiting to be found in the hand?

This is a remarkable paper, not only for the genes described but also for its original and inventive design. As already stated by the authors, two genes identified in these regions (PIK3C3 and NOS1AP) have already been implicated in schizophrenia. A number of others are convincing candidates and can be related to genes and processes relevant to the disease. For example, Chimaerin 1 (CHN1) (found in roh52) binds to the NMDA receptor subunit GRIN2A and regulates the morphology and density of dendritic spines (Van de Ven et al., 2005; Buttery et al., 2006). Dendritic spine density is reduced in the frontal cortex in schizophrenia (Glantz and Lewis, 2000). ATF6 (found in roh15) is a key player in the endoplasmic reticulum stress pathway and regulates the expression of another gene implicated in schizophrenia, XBP1 (Hirota et al., 2006).

Perhaps even more interesting is EIF2S1 (found in roh291). This is an eif2α subunit phosphorylated by four stress-responsive eif2α kinases that are themselves activated by viruses (pkr/EIF2AK2), starvation (gcn2/EIF2AK4), oxidative stress (hri/EIF2AK1), and endoplasmic reticulum stress (perk/EIF2AK3) (cf ATF6 and XBP1). Phosphorylated eif2α turns off protein synthesis by inhibiting the actions of the translation initiation factor eif2b, and also activates the transcription factor ATF4, that turns on a series of programs designed to counter the effects of these stressors, including genes controlling glutathione homoeostasis (Carter, 2007). ATF4 is a binding partner of DISC1 (Morris et al., 2003), while mutations in eif2b are responsible for a disease that selectively attacks oligodendrocytes, vanishing white matter disease (van der Knaap et al., 2006). Famine (Susser et al., 1996) and viral infections, for example, prenatal influenza (Sham et al., 1992), are risk factors for schizophrenia, and oxidative stress (Gysin et al., 2007) and endoplasmic reticulum stress (XBP1, ATF6) also play a role in its pathology. Oligodendrocyte cell loss is also prevalent in schizophrenia (Uranova et al., 2007).

EIF2S1 is thus at the hub of a network activated by environmental risk factors implicated in schizophrenia. The outputs of this network (eif2b and ATF4) regulate oligodendrocyte function and glutathione homoeostasis (inter alia). As a recent clinical trial has reported some benefit with the glutathione precursor N-acetyl cysteine, in schizophrenic patients (Lavoie et al., 2007), this network and the genes therein may be extremely pertinent.